CATCHUp Algorithm for Time-Dependent Vehicle Routing Index Compression
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Solution Overview
Problem
Existing vehicle routing techniques face challenges with large index sizes, slow query running times, and suboptimal path computations in time-dependent road networks, particularly due to the inefficiencies in contraction hierarchies and function-based representations of travel times.
Innovation Solution
The Customizable Approximated Time-dependent Contraction Hierarchies through Unpacking (CATCHUp) algorithm addresses these issues by using a more compact representation of travel time functions, storing only necessary unpacking information for shortcuts, and employing approximation during index construction to achieve fast and exact queries while reducing memory usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing vehicle routing techniques use traditional contraction hierarchies with function-based representations of travel times, then routing accuracy is maintained, but index size becomes large and query processing becomes slow
Solution Approach 1:
The patent transforms the representation of travel time functions from continuous functions to discrete time intervals with associated shortcut weights. This parameter transformation allows the system to maintain routing accuracy by preserving essential temporal information while dramatically reducing the storage requirements of the index structure.
Solution Approach 2:
The patent extracts only the necessary information from complete travel time functions, storing discrete time intervals and corresponding shortcut weights rather than full functional representations. This extraction approach maintains the critical data needed for accurate routing while eliminating redundant information that contributes to large index sizes.
2Measurement precision
If existing vehicle routing techniques use detailed function-based representations, then exact shortest paths can be computed, but query running time increases
Solution Approach 1:
By changing the parameter representation from continuous functions to discrete time intervals, the patent enables faster comparison and evaluation operations during query processing. The discrete representation allows for more efficient algorithmic operations while maintaining the ability to compute exact shortest paths through proper weighting of time-dependent shortcuts.
3Measurement precision
If traditional contraction hierarchies are used without approximation, then exact routing is achieved, but processing resources and memory usage increase
Solution Approach 1:
The patent extracts and stores only the essential temporal characteristics in discrete time intervals rather than maintaining complete function representations. This reduction in data structure complexity directly decreases memory usage and processing resource requirements while preserving the ability to compute exact routing solutions.
Data Source
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AI summary
The present disclosure provides a method for time-dependent vehicle routing. The method includes selecting an index based on a current time, wherein the index is associated with a time interval and a travel path between a first node and a second node, wherein the travel path is represented by a shortcut between the first node and the second node while bypassing at least one further node of the travel path; unpacking the shortcut to obtain individual time-dependent sub travel times for each sub-segment of a plurality of sub-segments of the travel path associated with the shortcut; and determining a travel time for the travel path based on the time-dependent sub travel times.